기계 학습에 대한 Wolfram 문서
Wolfram 기계 학습은 Wolfram 언어의 통합된 부분입니다. 전체 시스템은 면밀히 통합되어 완벽하게 함께 작동하는 모든 계산 — 영역을 커버하는 6,000개 이상의 내장 함수가 포함되어 있습니다.
전체 영역 및 문서
Predict ▪ Classify ▪ ActivePrediction ▪ SequencePredict ▪ Nearest ▪ FindFit ▪ FindClusters ▪ FeatureExtraction ▪ FeatureSpacePlot ▪ FeatureImpactPlot ▪ AnomalyDetection ▪ DimensionReduction ▪ MissingValueSynthesis ▪ LLMFunction ▪ LLMSynthesize ▪ ImageSynthesize ▪ ChatObject ▪ LLMPrompt ▪ LLMTool ▪ LLMConfiguration ▪ NetModel ▪ NetTrain ▪ NetGraph ▪ LinearLayer ▪ ConvolutionLayer ▪ AttentionLayer ▪ ImageIdentify ▪ ImageCases ▪ FindFaces ▪ TextRecognize ▪ ImageGraphics ▪ TextSummarize ▪ LanguageIdentify ▪ TextStructure ▪ TextCases ▪ SpeechRecognize ▪ AudioIdentify ▪ SpeechCases ▪ SpeakerMatchQ ▪ PitchRecognize ▪ NetChain ▪ NetMeasurements ▪ NetPort ▪ NetPortGradient ▪ NetStateObject ▪ NetTrainResultsObject ▪ ThreadingLayer ▪ AggregationLayer ▪ SoftmaxLayer ▪ NetReplacePart ▪ NetInitialize ▪ NetTake ▪ NetAppend ▪ NetReplace ▪ NetFlatten ▪ NetEncoder ▪ NetDecoder ▪ LLMResourceFunction ▪ ClusteringComponents ▪ ClusterClassify ▪ ClusteringMeasurements ▪ MeanShift ▪ NearestNeighborGraph ▪ Dendrogram ▪ ClusteringTree ▪ FindGraphCommunities ▪ CommunityGraphPlot ▪ ConnectedComponents ▪ FindGraphPartition ▪ FindClique ▪ FindKClique ▪ ImageForestingComponents ▪ WatershedComponents ▪ GrowCutComponents ▪ DistanceFunction ▪ ClusterDissimilarityFunction ▪ Weights ▪ PerformanceGoal ▪ CriterionFunction ▪ Method ▪ LocalModelFit ▪ KernelModelFit ▪ LinearModelFit ▪ NonlinearModelFit ▪ GeneralizedLinearModelFit ▪ LogitModelFit ▪ ProbitModelFit ▪ FittedModel ▪ Around ▪ BestFit ▪ FitResiduals ▪ ANOVA ▪ ParameterEstimate ▪ CookDistances ▪ Deviances ▪ AIC ▪ FitCurvatureTable ▪ DesignMatrix ▪ NominalVariables ▪ LinkFunction ▪ LinearOffsetFunction ▪ ConfidenceLevel ▪ VarianceEstimatorFunction ▪ DispersionEstimatorFunction ▪ FindFormula ▪ FindDistribution ▪
기계 학습 분야의 Wolfram 제품 사용 시작하기
Wolfram|One 또는 Mathematica에서 Wolfram 언어에 접근하기
